Approximately 60 000 people in England have coexisting type 2 diabetes mellitus (T2DM) and severe mental illness (SMI). They are more likely to have poorer health outcomes and require more complex care pathways compared with those with T2DM alone. Despite increasing prevalence, little is known about the healthcare resource use and costs for people with both conditions.

To assess the impact of SMI on healthcare resource use and service costs for adults with T2DM, and explore the predictors of healthcare costs and lifetime costs for people with both conditions.

This was a matched-cohort study using data from the Clinical Practice Research Datalink linked to Hospital Episode Statistics for 1620 people with comorbid SMI and T2DM and 4763 people with T2DM alone. Generalised linear models and the Bang and Tsiatis method were used to explore cost predictors and mean lifetime costs respectively.

There were higher average annual costs for people with T2DM and SMI (£1930 higher) than people with T2DM alone, driven primarily by mental health and non-mental health-related hospital admissions. Key predictors of higher total costs were older age, comorbid hypertension, use of antidepressants, use of first-generation antipsychotics, and increased duration of living with both conditions. Expected lifetime costs were approximately £35 000 per person with both SMI and T2DM. Extrapolating nationally, this would generate total annual costs to the National Health Service of around £250 m per year.

Our estimates of resource use and costs for people with both T2DM and SMI will aid policymakers and commissioners in service planning and resource allocation.

Depression treatments are typically less effective for young people than for adults. However, treatments rarely target loneliness, which is a key risk factor in the onset, maintenance and development of depression.

This study evaluated the efficacy of a novel loneliness intervention, Groups 4 Health (G4H), relative to the best-practice treatment of cognitive–behavioural therapy (CBT) in reducing loneliness and depression over a 12-month period (Australian New Zealand Clinical Trial Registry: ACTRN12618000440224).

The study was a phase 3 randomised non-inferiority trial comparing G4H with dose-controlled group CBT. Participants were 174 people aged 15–25 years experiencing loneliness and clinically significant symptoms of depression, who were not in receipt of adjunct treatment. Participants were recruited from mental health services in Southeast Queensland, Australia. Randomisation was conducted using computer software. Follow-up assessments and statistical analyses were masked to allocation. Both interventions consisted of five 75 min group-based psychotherapy sessions. The primary outcomes were depression and loneliness, with a non-inferiority margin of 2.20 for depression.

The trial enrolled 174 participants between 24 April 2018 and 25 May 2019, with 84 in the G4H condition and 90 in the CBT condition. All randomised participants were included in the intention-to-treat analyses (n = 174). The pre–post effect sizes for depression were dG4H = −0.71 and dCBT = −0.91. For loneliness, they were dG4H = −1.07 and dCBT = −0.89. At 12-month follow-up, the absolute difference between groups on depression was 1.176 (95% CI −1.94 to 4.29) and on loneliness it was −0.679 (95% CI −1.43 to 0.07). No adverse effects were observed.

G4H was non-inferior to CBT for depression and showed a slight advantage over CBT for loneliness that emerged after treatment completion.

There is concern that the COVID-19 pandemic and its aftermath will result in excess suicides by increasing known risk factors such as self-harm, but evidence on how pandemic-related risk factors contribute to changes in these outcomes is lacking.

To examine how different COVID-19-related experiences of and worries about adversity contribute to changes in self-harm thoughts and behaviours.

Data from 49 324 UK adults in the University College London COVID-19 Social Study were analysed (1 April 2020 to 17 May 2021). Fixed-effects regressions explored associations between weekly within-person variation in five categories of adversity experience and adversity worries with changes in self-harm thoughts and behaviours across age groups (18–29, 30–44, 45–59 and 60+ years).

In total, 26.1% and 7.9% of respondents reported self-harm thoughts and behaviours respectively at least once over the study period. The number of adverse experiences was more strongly related to outcomes than the number of worries. The largest specific adversity contributing to increases in both outcomes was having experienced physical or psychological abuse. Financial worries increased the likelihood of both outcomes in most age groups, and having had COVID-19 increased the likelihood of both outcomes in young (18–29 years) and middle-aged (45–59 years) adults.

Findings suggest that a significant portion of UK adults may be at increased risk for self-harm thoughts and behaviours during the pandemic. Given the likelihood that the economic and social consequences of the pandemic will accumulate, policy makers can begin adapting evidence-based suicide prevention strategies and other social policies to help mitigate its consequences.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Healthcare decision makers require accurate long-term economic models to evaluate the cost-effectiveness of new mental health interventions.

To assess the suitability of current patient-level economic models to estimate long-term economic outcomes in severe mental illness.

We undertook pre-specified systematic searches in MEDLINE, Embase and PsycINFO to identify reviews and stand-alone publications of economic models of interventions for schizophrenia, bipolar disorder and major depressive disorder (PROSPERO: CRD42020158243). We screened paper titles and abstracts to identify unique patient-level economic models. We conducted a structured extraction of identified models, recording the presence of key predefined model features. Model quality and validation were appraised using the 2014 ISPOR and 2016 AdViSHE model checklists.

We identified 15 unique patient-level models for psychosis and major depressive disorder from 1481 non-duplicate records. Models addressed schizophrenia (n = 6), bipolar disorder (n = 2) and major depressive disorder (n = 7). The predominant model type was discrete event simulation (n = 9). Model complexity and incorporation of patient heterogeneity varied considerably, and only five models extrapolated costs and outcomes over a lifetime horizon. Key model parameters were often based on low-quality evidence, and checklist quality assessment revealed weak model verification procedures.

Existing patient-level economic models of interventions for severe mental illness have considerable limitations. New modelling efforts must be supplemented by the generation of good-quality, contemporary evidence suitable for model building. Combined effort across the research community is required to build and validate economic extrapolation models suitable for accurately assessing the long-term value of new interventions from short-term clinical trial data.

Growing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset.

To examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders.

We identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008–2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods.

Following covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5–34%), 18% (95% CI 5–34%) and 11% (95% CI 3–19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25–38%), 31% (95% CI 24–37%), 7% (95% CI 4–11%) and 9% (95% CI 5–14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years.

Residential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.

Psychotic experiences predict adverse health outcomes, particularly if they are persistent. However, it is unclear what distinguishes persistent from transient psychotic experiences.

In a large population-based cohort, we aimed to (a) describe the course of hallucinatory experiences from childhood to adolescence, (b) compare characteristics of youth with persistent and remittent hallucinatory experiences, and (c) examine prediction models for persistence.

Youth were assessed longitudinally for hallucinatory experiences at mean ages of 10 and 14 years (n = 3473). Multi-informant-rated mental health problems, stressful life events, self-esteem, non-verbal IQ and parental psychopathology were examined in relation to absent, persistent, remittent and incident hallucinatory experiences. We evaluated two prediction models for persistence with logistic regression and assessed discrimination using the area under the curve (AUC).

The persistence rate of hallucinatory experiences was 20.5%. Adolescents with persistent hallucinatory experiences had higher baseline levels of hallucinatory experiences, emotional and behavioural problems, as well as lower self-esteem and non-verbal IQ scores than youth with remittent hallucinatory experiences. Although the prediction model for persistence versus absence of hallucinatory experiences demonstrated excellent discriminatory power (AUC-corrected = 0.80), the prediction model for persistence versus remittance demonstrated poor accuracy (AUC-corrected = 0.61).

This study provides support for the dynamic expression of childhood hallucinatory experiences and suggests increased neurodevelopmental vulnerability in youth with persistent hallucinatory experiences. Despite the inclusion of a wide array of psychosocial parameters, a prediction model discriminated poorly between youth with persistent versus remittent hallucinatory experiences, confirming that persistent hallucinatory experiences are a complex multifactorial trait.

Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics.

This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample.

We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients.

Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms.

Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.

An ‘ethnic’ or ‘group’ density effect in psychosis has been observed, whereby the risk of psychosis in minority group individuals is inversely related to neighbourhood-level proportions of others belonging to the same group. However, there is conflicting evidence over whether this effect differs between minority groups and limited investigation into other moderators.

To conduct a comprehensive systematic review and meta-analysis of the group density effect in psychosis and examine moderators.

Four databases were systematically searched. A narrative review was conducted and a three-level meta-analysis was performed. The potential moderating effect of crudely and specifically defined minority groups was assessed. Country, time, area size and whether studies used clinical or non-clinical outcomes were also tested as moderators.

Thirty-two studies were included in the narrative review and ten in the meta-analysis. A 10 percentage-point decrease in own-group density was associated with a 20% increase in psychosis risk (OR = 1.20, 95% CI 1.09−1.32, P < 0.001). This was moderated by crudely defined minority groups (F6,68 = 6.86, P < 0.001), with the strongest associations observed in Black populations, followed by a White Other sample. Greater heterogeneity was observed when specific minority groups were assessed (F25,49 = 7.26, P < 0.001).

This is the first review to provide meta-analytic evidence that the risk of psychosis posed by lower own-group density varies across minority groups, with the strongest associations observed in Black individuals. Heterogeneity in effect sizes may reflect distinctive social experiences of specific minority groups. Potential mechanisms are discussed, along with the implications of findings and suggestions for future research.

Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes.

We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation.

Mendelian randomisation uses genetic variants predictive of a certain ‘exposure’ as instrumental variables to test causal effects on an ‘outcome’. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods.

There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects.

Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.

Clozapine is associated with increased risk of myocarditis. However, many common side-effects of clozapine overlap with the clinical manifestations of myocarditis. As a result, there is uncertainty about which signs, symptoms and investigations are important in distinguishing myocarditis from benign adverse effects of clozapine. Clarity on this issue is important, since missing a diagnosis of myocarditis or discontinuing clozapine unnecessarily may both have devastating consequences.

To examine the clinical characteristics of clozapine-induced myocarditis and to identify which signs and symptoms distinguish true myocarditis from other clozapine adverse effects.

A retrospective analysis of the record database for 247 621 patients was performed. A natural language processing algorithm identified the instances of patients in which myocarditis was suspected. The anonymised case notes for the patients of each suspected instance were then manually examined, and those whose instances were ambiguous were referred for an independent assessment by up to three cardiologists. Patients with suspected instances were classified as having confirmed myocarditis, myocarditis ruled out or undetermined.

Of 254 instances in 228 patients with suspected myocarditis, 11.4% (n = 29 instances) were confirmed as probable myocarditis. Troponin and C-reactive protein (CRP) had excellent diagnostic value (area under the curve 0.975 and 0.896, respectively), whereas tachycardia was of little diagnostic value. All confirmed instances occurred within 42 days of clozapine initiation.

Suspicion of myocarditis can lead to unnecessary discontinuation of clozapine. The ‘critical period’ for myocarditis emergence is the first 6 weeks, and clinical signs including tachycardia are of low specificity. Elevated CRP and troponin are the best markers for the need for further evaluation.

The general health of children of parents with mental illness is overlooked.

To quantify the difference in healthcare use of children exposed and unexposed to maternal mental illness (MMI).

This was a retrospective cohort study of children aged 0–17 years, from 1 April 2007 to 31 July 2017, using a primary care register (Clinical Practice Research Datalink) linked to Hospital Episodes Statistics. MMI included non-affective/affective psychosis and mood, anxiety, addiction, eating and personality disorders. Healthcare use included prescriptions, primary care and secondary care contacts; inflation adjusted costs were applied. The rate and cost was calculated and compared for children exposed and unexposed to MMI using negative binomial regression models. The total annual cost to NHS England of children with MMI was estimated.

The study included 489 255 children: 238 106 (48.7%) girls, 112 741 children (23.0%) exposed to MMI. Compared to unexposed children, exposed children had a higher rate of healthcare use (rate ratio 1.27, 95% CI 1.26–1.28), averaging 2.21 extra contacts per exposed child per year (95% CI 2.14–2.29). Increased healthcare use among exposed children occurred in inpatients (rate ratio 1.37, 95% CI 1.32–1.42), emergency care visits (rate ratio 1.34, 95% CI 1.33–1.36), outpatients (rate ratio 1.30, 95% CI 1.28–1.32), prescriptions (rate ratio 1.28, 95% CI 1.26–1.30) and primary care consultations (rate ratio 1.24, 95% CI 1.23–1.25). This costs NHS England an additional £656 million (95% CI £619–£692 million), annually.

Children of mentally ill mothers are a health vulnerable group for whom targeted intervention may create benefit for individuals, families, as well as limited NHS resources.

There is currently major concern about the impact of the global COVID-19 outbreak on mental health. But it remains unclear how individual behaviours could exacerbate or protect against adverse changes in mental health.

To examine the associations between specific activities (or time use) and mental health and well-being among people during the COVID-19 pandemic.

Data were from the UCL COVID-19 Social Study, a panel study collecting data weekly during the COVID-19 pandemic. The analytical sample consisted of 55 204 adults living in the UK who were followed up for the 11-week strict lockdown period from 21 March to 31 May 2020. Data were analysed using fixed-effects and Arellano–Bond models.

Changes in time spent on a range of activities were associated with changes in mental health and well-being. After controlling for bidirectionality, behaviours involving outdoor activities such as gardening and exercising predicted subsequent improvements in mental health and well-being, whereas increased time spent following news about COVID-19 predicted declines in mental health and well-being.

These results are relevant to the formulation of guidance for people obliged to spend extended periods in isolation during health emergencies and may help the public to maintain well-being during future lockdowns and pandemics.

Complex traumas are traumatic experiences that involve multiple interpersonal threats during childhood or adolescence, such as repeated abuse. These traumas are hypothesised to cause more severe psychopathology and poorer cognitive function than other non-complex traumas. However, empirical testing has been limited to clinical/convenience samples and cross-sectional designs.

To investigate psychopathology and cognitive function in young people exposed to complex, non-complex or no trauma, from a population-representative longitudinal cohort, and to consider the role of pre-existing vulnerabilities.

Participants were from the Environmental Risk Longitudinal Twin Study, a population-representative birth cohort of 2232 British children. At age 18 years (93% participation), we assessed lifetime exposure to complex and non-complex trauma, past-year psychopathology and current cognitive function. We also prospectively assessed early childhood vulnerabilities: internalising and externalising symptoms at 5 years of age, IQ at 5 years of age, family history of mental illness, family socioeconomic status and sex.

Participants exposed to complex trauma had more severe psychopathology and poorer cognitive function at 18 years of age, compared with both trauma-unexposed participants and those exposed to non-complex trauma. Early childhood vulnerabilities predicted risk of later complex trauma exposure, and largely explained associations of complex trauma with cognitive deficits, but not with psychopathology.

By conflating complex and non-complex traumas, current research and clinical practice underestimate the severity of psychopathology, cognitive deficits and pre-existing vulnerabilities linked with complex trauma. A better understanding of the mental health needs of people exposed to complex trauma could inform the development of new, more effective interventions.

Recovery in schizophrenia is a complex process, involving clinical, societal and personal recovery. Until now, studies analysed these domains separately, without examining their mutual relations and changes over time.

This study aimed to examine different states of recovery and transition rates between states.

The Pharmacotherapy Monitoring and Outcome Survey (2006–2017) yearly assesses patients with schizophrenia in the Northern Netherlands. Data from 2327 patients with one up to 11 yearly measurements on clinical, societal and personal recovery were jointly analysed with a mixture latent Markov model (MLMM).

The selected MLMM had four states that differed in degree and pattern of recovery outcomes. Patients in state 1 were least recovered on any domain (16% of measurements), and partly recovered in states 2 (25%; featured by negative symptoms) and 3 (21%; featured by positive symptoms). Patients in state 4 (38%) were most recovered, except for work, study and housekeeping. At the subsequent measurement, the probability of remaining in the same state was 77–89%, transitioning to a better state was 4–12% and transitioning to a worse state was 4–6%; no transitions occurred between states 1 and 4. Female gender, shorter illness duration and less schizophrenia were more prevalent in better states.

Quite a high recovery rate was present among a substantial part of the measurements (38%, state 4), with a high probability (89%) of remaining in this state. Transition rates in the other states might increase to a more favourable state by focusing on adequate treatment of negative and positive symptoms and societal problems.

Schizophrenia is considered a polygenic disorder. People with schizophrenia and those with genetic high risk of schizophrenia (GHR) have presented with similar neurodevelopmental deficits in hemispheric asymmetry. The potential associations between neurodevelopmental abnormalities and schizophrenia-related risk genes in both schizophrenia and those with GHR remains unclear.

To investigate the shared and specific alternations to the structural network in people with schizophrenia and those with GHR. And to identify an association between vulnerable structural network alternation and schizophrenia-related risk genes.

A total of 97 participants with schizophrenia, 79 participants with GHR and 192 healthy controls, underwent diffusion tensor imaging (DTI) scans at a single site. We used graph theory to characterise hemispheric and whole-brain structural network topological metrics. For 26 people in the schizophrenia group and 48 in the GHR group with DTI scans we also calculated their schizophrenia-related polygenic risk scores (SZ-PRSs). The correlations between alterations to the structural network and SZ-PRSs were calculated. Based on the identified genetic–neural association, bioinformatics enrichment was explored.

There were significant hemispheric asymmetric deficits of nodal efficiency, global and local efficiency in the schizophrenia and GHR groups. Hemispheric asymmetric deficit of local efficiency was significantly positively correlated with SZ-PRSs in the schizophrenia and GHR groups. Bioinformatics enrichment analysis showed that these risk genes may be linked to signal transduction, neural development and neuron structure. The schizophrenia group showed a significant decrease in the whole-brain structural network.

The shared asymmetric deficits in people with schizophrenia and those with GHR, and the association between anomalous asymmetry and SZ-PRSs suggested a vulnerability imaging marker regulated by schizophrenia-related risk genes. Our findings provide new insights into asymmetry regulated by risk genes and provides a better understanding of the genetic–neural pathological underpinnings of schizophrenia.

Safety planning-type interventions (SPTIs) for patients at risk of suicide are often used in clinical practice, but it is unclear whether these interventions are effective.

This article reports on a meta-analysis of studies that have evaluated the effectiveness of SPTIs in reducing suicidal behaviour and ideation.

We searched Medline, EMBASE, PsycINFO, Web of Science and Scopus from their inception to 9 December 2019, for studies that compared an SPTI with a control condition and had suicidal behaviour or ideation as outcomes. Two researchers independently extracted the data. To assess suicidal behaviour, we used a random-effects model of relative risk based on a pooled measure of suicidal behaviour. For suicidal ideation, we calculated effect sizes with Hedges’ g. The study was registered at PROSPERO (registration number CRD42020129185).

Of 1816 unique abstracts screened, 6 studies with 3536 participants were eligible for analysis. The relative risk of suicidal behaviour among patients who received an SPTI compared with control was 0.570 (95% CI 0.408–0.795, P = 0.001; number needed to treat, 16). No significant effect was found for suicidal ideation.

To our knowledge, this is the first study to report a meta-analysis on SPTIs for suicide prevention. Results support the use of SPTIs to help preventing suicidal behaviour and the inclusion of SPTIs in clinical guidelines for suicide prevention. We found no evidence for an effect of SPTIs on suicidal ideation, and other interventions may be needed for this purpose.